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VMD on Tesla GPUs
VMD is a molecular visualization program for displaying, animating, and analyzing large biomolecular systems using 3-D graphics and built-in scripting. Several key kernels and applications in VMD now take advantage of the massively parallel CUDA architecture of NVIDIA’s GPUs. These applications run 20x to 100x faster when using a NVIDIA CUDA GPU compared to running them on a CPU only and are discussed below.
Download and Installation
- Download VMD 1.8.7 Binaries (from UIUC)
- Release Notes
Benchmark Data
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| Data courtesy of Theoretical and Computational Bio-physics Group, UIUC |
There are several detailed benchmarks on VMD using GPUs at NVIDIA’s VMD benchmark page.
Presentations
- Publications and presentations on GPU acceleration in VMD and NAMD by Klaus Schluten’s Group
- From SC09: Accelerating Molecular Modeling Applications with GPU Computing - John Stone, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign
- From 2009 GPU Technology Conference: GPU Accelerated Visualization and Analysis in VMD - John Stone, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign
- More publications on accelerating molecular dynamics applications using GPUs
Interviews / Videos
- From SC09: John Stone of University of Illinois Talks About Running VMD 412x Faster with GPUs
- SC09 BLOG on NVIDIA nTersect: Studying the H1N1 Virus using NVIDIA GPUs
Discussion Forums
GPU SOLUTIONS
The Tesla Bio Workbench applications can be deployed on GPU-based desktop personal supercomputers or in data center solutions. Built on the revolutionary massively parallel CUDA architecture, these solutions are designed to accelerate the pace of computational science.
RECOMMENDED HARDWARE CONFIGURATION
| Desktop Workstation Configuration | Data Center Configuration |
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WORKSTATION SOLUTIONS TESLA PERSONAL SUPERCOMPUTER For personal supercomputing at your desk
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DATA CENTER SOLUTIONS TESLA GPU COMPUTING CLUSTERS For computing with large-scale installations
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